Alarm method, system and storage medium for abnormalities of sample analyzer

ABSTRACT

A method, system and storage medium for providing an alarm for indicating that an abnormality is present in a sample analyzer are provided. The method includes: mixing a first aliquot of a blood sample with a diluent agent to prepare a first test sample; mixing a second aliquot of the blood sample with a lytic reagent to prepare a second test sample; detecting electrical impedance signals of the first test sample; detecting at least two types of optical signals of the second test sample; acquiring first platelet detection data based on the electrical impedance signals; acquiring second platelet detection data based on the at least two types of optical signals; acquiring an evaluation result based on a difference between the first platelet detection data and the second platelet detection data; determining whether the evaluation result meets a preset condition to provide an alarm.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/078,705, filed Oct. 23, 2020, which is a continuation ofInternational Application No. PCT/CN2019/084686, filed Apr. 26, 2019,which claims priority benefit of International Application No.PCT/CN2018/085198, filed Apr. 28, 2018, each of which is incorporatedherein by reference.

TECHNICAL FIELD

The present disclosure relates to the field of in vitro detection, andin particular, to a blood analyzer, a blood analysis system and ananalysis method for a blood sample and a storage medium thereof.

BACKGROUND ART

Blood analysis is widely used in medical research and detection toacquire related information about blood cells including red blood cells,white blood cells, platelets, etc. Commonly used automated bloodanalyzers generally analyze blood cells in blood samples based on theelectrical impedance principle (also known as Coulter Principle).According to the electrical impedance principle, when particlessuspended in an electrolyte pass through a detection aperture with theelectrolyte, the equivalent resistance across the detection aperturewill change. Under effect of a constant current source cross thedetection aperture, the voltage across the detection aperture willchange. The changes in the voltage across the detection aperture arecollected by a circuit system, and voltage pulse waveforms can thus begenerated, wherein amplitudes of the pulse waveforms reflect volumesizes of the particles. The analyzers can provide information aboutvolume distribution of particles in samples according to the acquiredpulse waveforms. For blood samples, the blood analyzers can provide avolume distribution histogram of blood cells in a test blood samplebased on the electrical impedance principle, and then acquire bloodanalysis data such as cell classification, cell count and the like byanalyzing the volume distribution histogram.

However, detection signals based on the electrical impedance principlecan only reflect information about volume of particles passing throughthe detection aperture, and cannot be used to differentiate amongdifferent particles with a same or similar volume. For example, bloodcell analysis methods based on the electrical impedance method cannot beused to differentiate among large platelets, red blood cell fragments(schistocytes) and microcytes with a similar volume, and the bloodanalyzers may mistakenly count a large platelet with relatively largevolume as a red blood cell, resulting in false decrease in largeplatelet detection results, and the blood analyzers may also mistakenlycount a red blood cell with relatively small volume (such as a red bloodcell fragment and a microcyte) as a platelet, resulting in falseincrease in platelet detection results. Moreover, in the automateddetection process for a large number of blood samples, insufficientcleaning of the detection channel between detections of different bloodsamples may also affect detection results of platelets. For example,impurity particles attached to the detection channel or uncleanedschistocytes from previous measured sample may be mixed with the presenttest blood sample, causing a false increase in platelet detectionresults. In some cases, platelets may be easily activated and attachedto the detection channel, causing a false increase in platelet detectionresults.

SUMMARY OF THE INVENTION

An aspect of embodiments of the present disclosure includes an alarmmethod for providing an alarm for indicating that an abnormality ispresent in a sample analyzer, the method including: providing a bloodsample; mixing a first aliquot of the blood sample with a diluent agentto obtain a first test sample for first platelet detection; mixing asecond aliquot of the blood sample with a lytic reagent to obtain asecond test sample for second platelet detection, wherein red bloodcells in the second test sample are lysed; detecting electricalimpedance signals of the first test sample; detecting at least two typesof optical signals of the second test sample; acquiring first plateletdetection data of the blood sample based on the electrical impedancesignals; acquiring second platelet detection data of the blood samplebased on the at least two types of optical signals; acquiring anevaluation result based on a difference between the first plateletdetection data and the second platelet detection data; determiningwhether the evaluation result meets a preset condition; and providing analarm for indicating that an abnormality is present in the firstplatelet detection and/or an abnormality is present in the step ofelectrical impedance signal detection of the sample analyzer, when theevaluation result meets the preset condition.

Acquiring second platelet detection data of the blood sample based onthe at least two types of optical signals may include: generating ascattergram of the second test sample based on the at least two types ofoptical signals; differentiating a white blood cell region from aplatelet region in the scattergram based on the at least two types ofoptical signals; and acquiring the second platelet detection data of theblood sample based on the platelet region.

The alarm method provided by embodiments of the present disclosure mayinclude: outputting a prompt that the abnormality of the first plateletdetection is caused by the abnormality in the step of the electricalimpedance signal detection and/or that the first platelet detectionresult is unreliable.

Further, in the alarm method provided by embodiments of the presentdisclosure, the lytic reagent includes a hemolytic agent for lysing redblood cells and a fluorescence dye for staining blood cells, and the atleast two types of optical signals include forward scattered lightsignals and fluorescent signals.

Further, in the alarm method provided by embodiments of the presentdisclosure, the lytic reagent comprises a hemolytic agent for lysing redblood cells, and the at least two types of optical signals comprisefirst scattered light signals and second scattered light signals,wherein the first scattered light signals are forward scattered lightsignals, and the second scattered light signal are at least one type ofmedium-angle scattered light signals and side scattered light signals.

Further, in the alarm method provided by embodiments of the presentdisclosure, acquiring the second platelet detection data of the bloodsample based on the platelet region includes: acquiring a derivedplatelet volume histogram based on the forward scattered light signalsof a particle population in the platelet region; or acquiring the secondplatelet detection data of the blood sample based on a number ofparticles in the platelet region.

Further, in the alarm method provided by embodiments of the presentdisclosure, the lytic reagent includes a hemolytic agent for lysing redblood cells and a fluorescence dye for staining blood cells, the atleast two types of optical signals include side scattered light signalsand fluorescent signals; and the second platelet detection data of theblood sample is acquired based on a number of particles in the plateletregion.

Further, in the alarm method provided by embodiments of the presentdisclosure, the platelet region includes a large platelet region, andthe second platelet detection data of the blood sample is acquired byusing the large platelet region.

Further, in the alarm method provided by embodiments of the presentdisclosure, the first platelet detection data includes at least onecharacteristic parameter of first platelet volume distribution data, andthe second platelet detection data includes at least one characteristicparameter of second platelet volume distribution data.

Further, in the alarm method provided by embodiments of the presentdisclosure, the characteristic parameter is selected from one or more ofa platelet count, a platelet volume histogram, a mean platelet volumeand a platelet volume distribution width; or the characteristicparameter is selected from one or more of a platelet count, a plateletvolume histogram, a mean platelet volume and a platelet volumedistribution width within a certain volume threshold range.

Further, in the alarm method provided by embodiments of the presentdisclosure, the two types of optical signals include scattered lightsignals and fluorescent signals, and the method further includesclassifying white blood cells into white blood cell subpopulations, orcounting white blood cells or identifying nucleated red blood cells orimmature cells or basophils according to the scattered light signals andthe fluorescent signals.

Further, in the alarm method provided by embodiments of the presentdisclosure, the two types of optical signals include first scatteredlight signals and second scattered light signals, wherein the firstscattered light signals are forward scattered light signals, and thesecond scattered light signals are at least one type of the medium-anglescattered light signals and side scattered light signals, and the methodfurther includes classifying white blood cells into white blood cellsubpopulations or identifying basophils according to the first scatteredlight signals and the second scattered light signals.

Further, in the alarm method provided by embodiments of the presentdisclosure, determining whether the evaluation result meets a presetcondition includes: comparing the first platelet detection data with thesecond platelet detection data to obtain a graphic difference degreetherebetween, determining whether the graphic difference degree meets apreset condition; or acquiring numerical information of the firstplatelet detection data and the second platelet detection data,calculating an evaluation value by using the numerical information,wherein the evaluation value is used to reflect a difference degreebetween the first platelet detection data and the second plateletdetection data; and determining whether the evaluation value meets apreset condition.

Further, the alarm method provided by embodiments of the presentdisclosure further includes the following steps: outputting the firstplatelet detection data if there is no alarm for abnormality; oroutputting the second platelet detection data if there is an alarm forabnormality.

Further, the alarm method provided by embodiments of the presentdisclosure may include continuously recording and counting determinationresults of evaluation values of platelet detection for a plurality ofblood samples, and providing an alarm for indicating that an abnormalityis present in the electrical impedance signal detection when thecontinuous determination results of the plurality of blood samples areyes.

An aspect of embodiments of the present disclosure includes anon-volatile computer-readable storage medium with a computer programstored thereon, wherein the computer program, when executed by aprocessor, implements steps of any alarm method mentioned above.

An aspect of embodiments of the present disclosure includes a bloodanalysis system, including: a sample treatment device comprising atleast one mixing chamber for mixing a first aliquot of a blood samplewith a diluent agent to prepare a first test sample for first plateletdetection, and for mixing a second aliquot of the blood sample with alytic reagent to prepare a second test sample for second plateletdetection, wherein red blood cells in the second test sample are lysed;a sample detection device comprising an electrical impedance detectionunit and an optical detection unit, wherein the electrical impedancedetection unit includes an aperture and an electrical impedancedetector, and the electrical impedance detector is configured to detectelectrical impedance signals of the first test sample passing throughthe aperture, and the optical detection unit includes an optical flowchamber, a light source and an optical detector, wherein the opticalflow chamber is in fluid communication with the mixing chamber, thelight source is configured to direct a light beam to the optical flowchamber, and the optical detector is configured to detect at least twotypes of optical signals of the second test sample passing through theoptical flow chamber; a data analysis module comprising a signalacquisition module, a classification and counting module and an alarmmodule; wherein the signal acquisition module is configured to acquirethe electrical impedance signals of the first test sample and the atleast two types of optical signals of the second test sample; theclassification and counting module is configured to acquire firstplatelet detection data of the blood sample based on the electricalimpedance signals, generate a scattergram of the second test samplebased on the at least two types of optical signals, differentiate awhite blood cell region from a platelet region in the scattergram basedon the at least two types of optical signals, and acquire secondplatelet detection data of the blood sample based on the plateletregion; and

the alarm module is configured to acquire an evaluation result based ona difference between the first platelet detection data and the secondplatelet detection data, determine whether the evaluation result meets apreset condition, and provide an alarm for indicating that anabnormality is present in the first platelet detection and/or anabnormality is present in the electrical impedance detection unit, whenthe evaluation result meets the preset condition.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the classification and counting module is configuredto: generate a scattergram of the second test sample based on the atleast two types of optical signals; differentiate a white blood cellregion from a platelet region in the scattergram based on the at leasttwo types of optical signals; and acquire the second platelet detectiondata of the blood sample based on the platelet region.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the alarm module is configured to output a promptthat the abnormality of the first platelet detection is caused by theabnormality in the electrical impedance detection unit and/or that thefirst platelet detection result is unreliable.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the lytic reagent includes a hemolytic agent forlysing red blood cells and a fluorescence dye for staining blood cells,the at least two types of optical signals include forward scatteredlight signals and fluorescent signals, and the optical detection unitincludes at least one scattered light detector and at least onefluorescent detector.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the dissolution reagent includes a hemolytic agentfor lysing red blood cells, and the at least two types of opticalsignals include first scattered light signals and second scattered lightsignals, wherein the first scattered light signals are forward scatteredlight signals, and the second scattered light signals are at least onetype of medium-angle scattered light signals and side scattered lightsignals, and the optical detection unit includes at least two scatteredlight detectors.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the classification and counting module is configuredto acquire a derived platelet volume histogram based on at least theforward scattered light signals of a particle population in the plateletregion; or the classification and counting module is configured toacquire the second platelet detection data of the blood sample based ona number of particles in the platelet region.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the lytic reagent includes a hemolytic agent forlysing red blood cells and a fluorescence dye for staining blood cells,the at least two types of optical signals include side scattered lightsignals and fluorescent signals; and the classification module isconfigured to acquire the second platelet detection data of the bloodsample based on a number of particles in the platelet region.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the platelet region includes a large plateletregion, the second platelet detection data includes second largeplatelet data, and the second platelet detection data of the bloodsample is acquired by using the large platelet region.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the first platelet detection data includes at leastone characteristic parameter of first platelet volume distribution data,and the second platelet detection data includes at least onecharacteristic parameter of second platelet volume distribution data.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the characteristic parameter is selected from one ormore of a platelet count, a platelet volume histogram, a mean plateletvolume and a platelet volume distribution width; or the characteristicparameter is selected from one or more of a platelet count, a plateletvolume histogram, a mean platelet volume and a platelet volumedistribution width within a certain volume threshold range.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the two types of optical signals include scatteredlight signals and fluorescent signals, and the classification andcounting module is further configured to classify white blood cells intowhite blood cell subpopulations, or count white blood cells or identifynucleated red blood cells or immature cells or basophils according tothe scattered light signals and the fluorescent signals.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the two types of optical signals include firstscattered light signals and second scattered light signals, wherein thefirst scattered light signals are forward scattered light signals, andthe second scattered light signals are at least one type of medium-anglescattered light signals and side scattered light signals, and theclassification and counting module is further configured to classifywhite blood cells into white blood cell subpopulations or identifybasophils according to the first scattered light signals and the secondscattered light signals.

Further, in the blood analysis system provided by embodiments of thepresent disclosure, the alarm module is configured to: compare the firstplatelet detection data with the second platelet detection data toobtain a graphic difference degree therebetween, determine whether thegraphic difference degree meets a preset condition; or acquire numericalinformation of the first platelet detection data and the second plateletdetection data, calculate an evaluation value by using the numericalinformation, wherein the evaluation value is used to reflect adifference degree between the first platelet detection data and thesecond platelet detection data; and determine whether the evaluationvalue meets a preset condition.

Further, the blood analysis system provided by embodiments of thepresent disclosure further includes a user interface for: outputting thefirst platelet detection data if there is no alarm for abnormality; oroutputting the second platelet detection data if there is an alarm forabnormality.

The method and system and the storage medium provided by the presentdisclosure can provide users with more abundant detection information,and remind users to perform a reexamination or recheck on plateletdetection data having an abnormality, thereby increasing accuracy ofplatelet detection.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of function modules of a blood analysissystem provided by the present disclosure.

FIG. 2 is a schematic diagram of function modules of a sample detectiondevice of the blood analysis system shown in FIG. 1 .

FIG. 3 is a flowchart of an alarm method provided by the presentdisclosure.

FIG. 4A is a scattergram generated by an embodiment of a secondexemplary implementation of the present disclosure. FIG. 4B is apartially enlarged view of a platelet region P in FIG. 4A. FIG. 4C is aderived volume histogram acquired based on the platelet region P in FIG.4A.

FIG. 5A is a schematic diagram for illustrating comparison between firstand second platelet detection data under normal detection. FIG. 5B is aschematic diagram for illustrating comparison between first and secondplatelet detection data under abnormal detection.

FIG. 6A is a scattergram generated by an embodiment of a third exemplaryimplementation of the present disclosure. FIG. 6B is a derived volumehistogram acquired based on the platelet region P′ in FIG. 6A.

FIG. 7A is a forward scattered light (FSC)-fluorescence (FL) scattergramof a second test sample stained by Alexa Fluor 488 dye. FIG. 7B is anFSC-FL scattergram of a second test sample stained by Mitotracker Reddye. FIG. 7C is an FSC-FL scattergram of a second test sample stained byRhodamine 123 dye. FIG. 7D is an FSC-FL scattergram of a second testsample stained by Mitotracker Deep Red dye.

FIG. 8A is a scattergram of a second test sample acquired by anembodiment of a fourth exemplary implementation of the presentdisclosure. FIG. 8B is a scattergram of a second test sample acquired byan embodiment of a fifth exemplary implementation of the presentdisclosure.

FIG. 9 is a schematic diagram for illustrating the differentiation of aplatelet region in a scattergram according to an embodiment of the fifthexemplary implementation of the present disclosure.

FIG. 10 is an overall stereoscopic diagram of a blood analysis systemprovided by the present disclosure.

FIG. 11 is an SFL-SSC-FSC three-dimensional (3D) scattergram of secondplatelet detection according to an implementation of the presentdisclosure.

FIG. 12 is an FSC-SSC-SFL 3D scattergram of second platelet detection ofa blood sample containing immature cells according to an implementationof the present disclosure.

FIG. 13 is an FSC-SFL scattergram of second platelet detection of ablood sample containing nucleated red blood cells according to animplementation of the present disclosure.

FIG. 14 is a platelet distribution region diagram corresponding to anSFL-SSC scattergram acquired by second platelet detection according toan implementation of the present disclosure.

LIST OF REFERENCE NUMERALS

Sample collection unit 10 Sample treatment device 30 Mixing chamber 320,320a, 320b Sample detection device 50 Electrical impedance detectionunit 51 Aperture 512 Electrical impedance detector 514 Optical detectionunit 53 Optical flow chamber 532 Light source 534 Optical detector 536Bus 60 Data analysis module 70 Storage system 710 Processor 730 Signalacquisition module 750 Classification and counting module 770 Alarmmodule 790 User interface 90 First housing 100 Second housing 200

The present disclosure will be further illustrated by the followingdetailed embodiments in combination with the drawings.

DETAILED DESCRIPTION OF EMBODIMENTS

The technical solution of the present disclosure will be described belowwith reference to preferred implementations and embodiments of thepresent disclosure. It should be noted that when one unit is describedas being “connected” to another unit, it may be directly connected toanother unit or an intermediate unit may exist at the same time. Whenone unit is described as being “arranged” on another unit, it may bedirectly arranged on another unit or an intermediate unit may exist atthe same time. Unless otherwise defined, all technical and scientificterms used herein have the same meaning as commonly understood by thoseskilled in the art to which this disclosure belongs. Names of elementsor apparatuses used in the specification of the present disclosure areonly intended to illustrate the specific embodiments instead of limitingthe present disclosure.

A first aspect of the present disclosure relates to a method, system andstorage medium for providing an alarm for indicating an abnormality ofplatelet detection and/or an abnormality of impedance channel by usingelectrical impedance signals, scattered light signals and fluorescentsignals of a blood sample.

FIG. 1 is a schematic diagram of a blood analysis system. The bloodanalysis system includes a sample collection unit 10, a sample treatmentdevice 30, a sample detection device 50, a data analysis module 70 and auser interface 90. The blood analysis system is provided with a liquidflow system (not shown in the figure), which is configured to make thesample collection unit 10, the sample treatment device 30 and the sampledetection device 50 in fluid communication for fluid transfer.

The sample collection unit 10 is configured to supply a blood sample tothe sample treatment device 30. The sample treatment device 30 isconfigured to treat the blood sample for preparing a test sample, andsupply the test sample to the sample detection device 50. The sampletreatment device 30 may include one or more mixing chambers forpreparing the test blood sample into one or more test samples. Thesample detection device 50 is configured to detect characteristics ofparticles in each test sample, and to acquire corresponding detectionsignals. The data analysis module 70 may be, directly or indirectly,connected electrically with the sample collection unit 10, the sampletreatment device 30, the sample detection device 50 and the userinterface 90 via a bus 60 to transmit and exchange data or signals.

In a first exemplary implementation of the present disclosure, thesample treatment device 30 includes at least one mixing chamber, whichis configured to mix a first aliquot of the test blood sample with adiluent agent to obtain a first test sample, and after cleaning to mix asecond aliquot of the test blood sample with a lytic reagent to obtain asecond test sample. Alternatively, the sample treatment device 30 mayfurther include a sample dispenser, which is configured to dispense thetest blood sample into several aliquots. Each aliquot of blood sample istransferred to the same mixing chamber or different mixing chambers andthen treated for subsequent detection. Alternatively, the sampletreatment device 30 includes a first mixing chamber 320 a and a secondmixing chamber 320 b for respectively preparing the first test sampleand the second test sample. Alternatively, the sample treatment device30 may include only one mixing chamber for preparing the first testsample and the second test sample one after another.

Specifically, the diluent agent for preparing the first test sample isgenerally used for diluting blood samples to detect red blood cells andplatelets by automated blood analyzers. The diluent agent generallyincludes one or more salts, such as an alkali metal salt, and isadjusted to be isotonic to maintain volumes of red blood cells. In theimplementation of the present disclosure, commercially available diluentagents may be used to dilute the first aliquot of the blood sample toform the first test sample. The commercially available diluent agentsinclude but not limited to M-68DS diluent agent, M-53D diluent agent,etc. which are produced by Shenzhen Mindray Bio-Medical Electronics Co.,Ltd. (Shenzhen, China). Temperature and/or stirring conditions forpreparing the first test sample may be the same as or similar to samplepreparation conditions used by existing automated blood analyzers fordetecting red blood cells and platelets.

Specifically, in the first aspect of the present disclosure, the lyticreagent includes a hemolytic agent and a fluorescence dye. The hemolyticagent may be any one of existing hemolytic agents for classifying whiteblood cells by automated blood analyzers, wherein the hemolytic agentmay be any one of a cationic surfactant, a nonionic surfactant, ananionic surfactant and an amphiphilic surfactant or any combinationthereof. The fluorescence dye is used for staining blood cells. In someembodiments of the implementation, the fluorescence dye may be a nucleicacid dye, thereby classifying nucleated blood cells, such as white bloodcells or nucleated red blood cells, and other types of cells bymeasuring the differences in scattered light signals and fluorescentsignals. In an embodiment of the implementation, the lytic reagent maybe prepared by using the lytic reagent formula disclosed in U.S. Pat.No. 8,367,358, the entire disclosure of which is incorporated herein byreference. The lytic reagent disclosed in U.S. Pat. No. 8,367,358includes a cationic cyanine compound (a fluorescence dye), a cationicsurfactant, a nonionic surfactant and an anionic compound. The lyticreagent may be used to lyse red blood cells and classify white bloodcells into their subpopulations by detecting differences in scatteredlight intensities and fluorescence intensities. Other existingfluorescence dyes may also be used in the lytic reagent, for example,the fluorescence dye described in U.S. Pat. No. 8,273,329, the entiredisclosure thereof is incorporated herein by reference, such a reagentmay be adopted to lyse red blood cells and identify nucleated red bloodcells by detecting differences in fluorescence intensities and scatteredlight intensities. Those skilled in the art may understand that thefluorescence dye may be contained in a separate staining solution, andsuch a staining solution can be used together with the hemolytic agentwithout a fluorescence dye. The staining solution may be added to theblood sample in the mixing chamber 320 before, after or upon thehemolytic agent is added for preparing the second test sample.Temperature and/or stirring conditions for preparing the second testsample may be the same as or similar to sample preparation conditionsused by existing automated blood analyzers for classifying white bloodcells.

In the first exemplary implementation, the sample detection device 50 ofthe blood analysis system includes an electrical impedance detectionunit 51 and an optical detection unit 53. FIG. 2 is a schematic diagramof function modules of the sample detection device 50.

The electrical impedance detection unit 51 is configured to detectelectrical impedance signals of the first test sample. The electricalimpedance detection unit 51 includes an aperture 512 and an electricalimpedance detector 514. The electrical impedance detector 514 isconfigured to detect electrical impedance signals of the first testsample when passing through the aperture, such as direct current (DC)impedance signals. It can be understood that, when a particle (or ablood cell) suspended in a conductive solution passes through theaperture, an electrical impedance signal can be detected due toimpedance change. The shape, amplitude and width of the pulse generatedby the electrical impedance signal are directly related to the size orvolume of the particle, and can be converted into the volume of thesubject particle. When two or more types of particles with differentsizes are detected, a frequency histogram acquired by an electricalimpedance detection can reflect a size distribution of these particles.In the prior art, U.S. Pat. Nos. 2,656,508 and 3,810,011 describemethods for automatically detecting blood cells by a blood analyzerprovided with an electrical impedance unit, the entire disclosure ofwhich is incorporated herein by reference.

The optical detection unit 53 includes a sheath flow system, an opticalflow chamber 532, a light source 534, an optical detector 536 and acorresponding detection circuit. The optical flow chamber 532 isoperatively in fluid communication with the mixing chamber 320, so thatthe first test sample is transferred by the sheath flow system from themixing chamber 320 to the optical flow chamber 532. The light source 534is configured to direct a light beam to the optical flow chamber 532.The optical detector 536 is configured to detect at least two types ofoptical signals of the first test sample. In the first exemplaryimplementation of the present disclosure, the at least two types ofoptical signals include forward scattered light signals and fluorescentsignals. In an embodiment, the optical detector 536 of the opticaldetection unit 53 is set to be suitable for detecting the forwardscattered light signals and the fluorescent signals of the first testsample passing through the optical flow chamber 532. In anotherembodiment, the at least two types of optical signals further includeside scattered light signals, and the optical detector 536 is set to besuitable for detecting the forward scattered light signals, the sidescattered light signals and the fluorescent signals of the first testsample passing through the optical flow chamber 532.

Herein, the optical flow chamber refers to a focused-flow flow chambersuitable for detecting scattered light signals and fluorescent signals,for example, the optical flow chambers used in existing flow cytometersand blood analyzers. When a particle, such as a blood cell, passesthrough an orifice of the optical flow chamber, the incident light beamemitted from the light source and directed to the orifice is scatteredby the particle in all directions. By arranging an optical detector atone or more angles with regard to the incident light beam, the lightscattered by the particle can be detected to acquire scattered lightsignals. Since different blood cell populations have different lightscattering properties, the scattered light signals can be used todifferentiate different cell populations. Specifically, the scatteredlight signals detected near the incident beam are generally referred toas forward scattered light signals or small-angle scattered lightsignals. In some embodiments, the forward scattered light signals may bedetected at an angle range from about 1° to about with respect to theincident beam. In some other embodiments, the forward scattered lightsignals may be detected at an angle range from about 2° to about 6° withrespect to the incident beam. Scattered light signals detected at anangle of about 90° with respect to the incident beam are generallyreferred to as side scattered light signals. In some embodiments, theside scattered light signals may be detected at an angle range fromabout to about 115° with respect to the incident beam. Generally,fluorescent signals emitted from blood cells stained by a fluorescencedye may also be detected at an angle of about with respect to theincident beam.

The data analysis module 70 includes a storage system 710 and aprocessor 730. The storage system 710 may store basic programs and datastructures for implementing various functions of the methods disclosedherein. The storage system 710 may include one or more memories and oneor more non-transitory computer-readable storage media. Thenon-transitory computer-readable storage media may include a Hard DiskDrive (HDD), a floppy disk, an optical disk, a Secure Digital MemoryCard (SD Card), a flash memory card or the like. The memory may includea primary Random Access Memory (RAM) for storing program instructionsand data or a Dynamic RAM (DRAM) and a Read Only Memory (ROM) forstoring fixed instructions. The non-transitory computer-readable storagemedium stores computer programs for implementing the methods disclosedby the present disclosure. The processor 730 includes, but is notlimited to, a Central Processing Unit (CPU), a Micro Controller Unit(MCU) and other devices for interpreting computer instructions andprocessing data in computer software. The processor 730 is configured toexecute various computer programs in the non-transitorycomputer-readable storage medium, thereby enabling the blood analysissystem to execute the corresponding detection process, analyze andprocess the at least two types of optical signals detected by the sampledetection device 50 in a real-time manner. In exemplary embodiments, theat least two types of optical signals may be processed by aField-Programmable Gate Array (FPGA), a Digital Signal Processor (DSP)or CPU, and then automatically analyzed by the computer programs toacquire related data of platelets and/or platelet subpopulations.

As shown in FIG. 1 , in the first exemplary implementation, the dataanalysis module 70 further includes a signal acquisition module 750, aclassification and counting module 770 and an alarm module 790. Thesignal acquisition module 750 is operatively connected with the sampledetection device 50. The signal acquisition module 750 may respectivelyacquire the electrical impedance signals of the first test sample andthe forward scattered light signals and the fluorescent signals of thesecond test sample. The classification and counting module 770 isconnected to the signal acquisition module 750. The classification andcounting module 770 acquires first platelet detection data of the bloodsample based on the electrical impedance signals. The classification andcounting module 770 generates a scattergram of the second test samplebased on the at least two types of optical signals, differentiates awhite blood cell region from a platelet region in the scattergram, andthen acquires second platelet detection data of the blood sample basedon the platelet region in the scattergram. It should be noted that thescattergram herein may be presented not only in a graphical form, butalso in a data array form, for example, in a numeric form of a table ora list with the same or similar resolution as the scattergram orhistogram, or may be presented in any other appropriate manner known inthe art. The alarm module 790 is connected to the classification andcounting module 770. The alarm module 790 acquires an evaluation resultbased on a difference between the first platelet detection data and thesecond platelet detection data. The alarm module 790 determines whetherthe evaluation result meets a preset condition, and the alarm module 790provides an alarm for indicating that the first platelet detection isabnormal and/or the impedance detection is abnormal when thedetermination result is yes, namely when the evaluation result meets thepreset condition. The steps of specific methods executed by theclassification and counting module 770 and the alarm module 790 will bedescribed in detail later.

The user interface 90 is a medium for interaction and informationexchange between the blood analysis system and users. The user interface90 may display blood analysis data acquired by the classification andcounting module 770 and/or an alarming signal for an abnormalityacquired by the alarm module 790 to the users of the blood analysissystem. In an embodiment, the user interface 90 may be a touch screen,which can identify touch control operations from users and displaydetection results. In another embodiment, the user interface 90 mayinclude an input device and an output device. The input device may be adata input medium that is electrically connected to the data analysismodule 70, such as a keyboard, a mouse and a microphone, etc. The outputdevice may be a display screen, a printer, a speaker, an indicatorlight, etc. It can be understood that, when the alarm module 790provides an alarm for an abnormality, the user interface may promptusers that the first platelet detection of the blood sample is abnormaland/or the electrical impedance detection of the sample analyzer isabnormal, by differentially marking the blood sample with colors, fontsor labels in a detection report or a displayed detection image, or byflashing, sound or other manners.

An alarm method provided by a second exemplary implementation of thepresent disclosure will be further described below with reference to thefunction modules of the blood analysis system described in the firstexemplary implementation. The alarm method may be used automated bloodanalyzers, or may also be used in blood analysis systems provided with aflow cytometer and an electrical impedance detector. The alarm methodmay be executed by a processor in the form of computer programs. Thecomputer programs may be provided in the automated blood analyzers, ormay be independently provided in a computer that can directly orindirectly acquire blood cell detection signal data.

Please refer to the flowchart shown in FIG. 3 . In the second exemplaryimplementation, the alarm method for providing an alarm for indicatingthat an abnormality is present in the sample analyzer includes thefollowing steps:

Step S200: providing a blood sample.

Step S220: mixing a first aliquot of the blood sample with a diluentagent to obtain a first test sample for first platelet detection.

Step S225: mixing a second aliquot of the blood sample with a lyticreagent to obtain a second test sample for second platelet detection,wherein the lytic reagent includes a hemolytic agent for lysing redblood cells and a fluorescence dye for staining blood cells.

Step S230: detecting electrical impedance signals of the first testsample.

Step S235: detecting at least two types of optical signals of the secondtest sample, wherein the at least two types of optical signals includeforward scattered light signals and fluorescent signals.

Step S250: acquiring first platelet detection data of the blood samplebased on the electrical impedance signals acquired at step S230.

Step S255: acquiring second platelet detection data of the blood samplebased on the at least two types of optical signals acquired at stepS235.

Step S270: acquiring an evaluation result based on a difference betweenthe first platelet detection data and the second platelet detectiondata.

Step S280: determining whether the evaluation result meets a presetcondition. When the determination result is yes, step S290 is executedto provide an alarm for indicating that the first platelet detection isabnormal and/or the electrical impedance signal detection is abnormal.When the determination result is no, the process ends.

In a specific implementation, when the processor executes step S200, thesample collection unit 10 supplies the blood sample to the bloodanalysis system or the blood analyzer. When the processor executes stepsS220 and S225, the sample treatment device respectively prepares thefirst test sample and the second test sample. Reagents and preparationconditions for preparing the first test sample and the second testsample have been described in detail above, which will not be repeatedherein. When the processor executes step S230, the electrical impedancedetection unit 51 of the sample detection device 50 detects theelectrical impedance signals of the first test sample; when theprocessor executes step S235, the optical detection unit 53 of thesample detection device detects the at least two types of opticalsignals of the second test sample. When the processor executes stepsS250 and S255, the data analysis module 70 respectively acquires thefirst and second platelet detection data. When the processor furtherexecutes steps S270-S290, the alarm module 790 of the data analysismodule 70 determines whether the platelet detection is abnormal based onthe first and second platelet detection data, and provides an alarm forthe abnormality. It can be understood that, in the flow of the steps foralarming an abnormality, steps S220, S230 and S250 for acquiring thefirst platelet detection data and steps S225, S235 and S255 foracquiring the second platelet detection data may be executed in parallelor in sequence.

At step S250, those skilled in the art should understand that, anelectrical impedance volume histogram of platelets and red blood cellsin the first test sample may be generated based on the electricalimpedance signals acquired at step S230. Generally, in the electricalimpedance volume histogram, volumes of blood cells are measured infemtoliter (fL). A distribution curve of platelets can be differentiatedfrom that of red blood cells in the volume histogram by one or morepreset volume boundary values, and then characteristic parameters ofplatelets in the blood sample can be acquired based on the distributioncurve of platelets. The one or more preset volume boundary values areempirical values or values that can be dynamically acquired based onempirical algorithm. In an embodiment, a volume range threshold fordifferentiating platelets may be 2-30 fL. The characteristic parametersof platelets include but not limited to platelet count (PLT), MeanPlatelet Volume (MPV), Platelet Distribution Width (PDW). It should benoted that “first platelet detection data” herein includes volumedistribution data of platelets and/or characteristic parametersreflecting volume distribution of platelets. The volume distributiondata of platelets may be expressed in a numeric form, or in a graphicalform.

At step S255, the present disclosure discloses a method for acquiringthe second platelet detection data based on the at least two types ofoptical signals of the second test sample. In the first aspect of thepresent disclosure, red blood cells in the second test sample are lysedand blood cells in the second test sample are stained by thefluorescence dye, and the at least two types of optical signals includeforward scattered light signals and fluorescent signals. Specifically,step S255 may include the following steps.

Step S2551: acquiring the at least two types of optical signals of thesecond test sample. Accordingly, for the blood analysis system in thefirst exemplary implementation, the signal acquisition module 750acquires the at least two types of optical signals of the second testsample.

Step S2553: generating a scattergram of the second test sample based onthe at least two types of optical signals. In an embodiment shown inFIG. 4A, an FL-FSC two-dimensional scattergram may be acquired based onintensities of the forward scattered light signals and the fluorescentsignals of the second test sample. Accordingly, for the blood analysissystem in the first exemplary implementation, the classification andcounting module 770 generates the scattergram of the second test sample.In an alternative implementation, the at least two types of opticalsignals acquired at step S235 include forward scattered light signals,side scattered light signals and fluorescent signals, and thescattergram generated at step S2553 may also be an FSC-SSC scattergram,an FL-SSC scattergram, or a FL-FSC-SSC 3D scattergram. It can beunderstood that, when the at least two types of optical signals includeother optical signals (such as medium-angle scattered light signals andfluorescent signals), the scattergram may also be 2D or 3D scattergramof other form. It can be understood that, the abscissa and ordinate ofthe scattergram may also be other parameters of forward scattered lightsignals and side scattered light signals that reflect particlecharacteristics of the first test sample, and the abscissa and ordinateof the scattergram may also be nonlinear coordinate axis, such aslogarithmic coordinate axis, to further highlight differences indistribution among particle populations.

Step S2555: differentiating a white blood cell region from a plateletregion in the scattergram of the second test sample based on the atleast two types of optical signals. Accordingly, for the blood analysissystem in the first exemplary implementation, the classification andcounting module 770 differentiates a white blood cell region from aplatelet region in the scattergram of the second test sample based onthe at least two types of optical signals. Taking the embodiment shownin FIG. 4A as an example, the white blood cell region W and the plateletregion P can be differentiated from each other in the scattergram basedon differences in intensities of the forward scattered light signals andthe fluorescent signals of the second test sample. The white blood cellregion W includes a region where white blood cells appear in thescattergram, and the platelet region P includes a region where plateletsappear in the scattergram. Those skilled in the art should understandthat the white blood cell region W and the platelet region P may be setby a gating technique.

As shown in FIG. 4A, in the prior art, it is generally believed that inparticle populations characterized by an optical scatter diagram of ahemolyzed blood sample, the particle population with relatively smallscattered light intensities and fluorescence intensities mainly includesschistocytes and platelets. The inventors have found after repeatedassumptions and experiments that, the lytic reagent may include one ormore types of lytic agents for lysing red blood cells and a fluorescencedye for staining nucleated blood cells, platelets treated by thehemolytic agent are different in volume sizes and cellular contents fromschistocytes and white blood cells, and a part of or all of plateletscan be differentiated in the hemolyzed blood sample by an optical method(for example, by measuring scattered light signals and fluorescentsignals).

In the second exemplary implementation, the platelet region Pdifferentiated at step S2555 may include impurity particles such asschistocytes. As shown in FIG. 4A, the intensities of the forwardscattered light signals of the platelet region P are substantially lessthan that of the white blood cell region W, and the intensities of thefluorescent signals of the platelet region P are substantially less thanthat of the white blood cell region W. FIG. 4B is a partially enlargedview of FIG. 4A, which is acquired by enlarging the platelet region P inthe scattergram shown in FIG. 4A.

Step S2557: acquiring the second platelet detection data of the bloodsample based on the platelet region P. Accordingly, for the bloodanalysis system in the first exemplary implementation, theclassification and counting module 770 acquires the second plateletdetection data of the blood sample based on the platelet region P.

In an implementation, at step S2557, the second platelet detection dataof the test blood sample is calculated based on the forward scatteredlight signals of a particle population characterized in platelets 10 b.

In an embodiment, the volume (Vol) of each particle characterized in theplatelets 10 b may be calculated by using Equation (1):

Vol _(a) =α*FSC  Equation (1)

-   -   wherein, FSC is the intensity of forward scattered light signal        of each particle (also referred to as “individual event”)        characterized in the platelets 10 b, and α is a constant.

In another embodiment, the volume (Vol) of each particle characterizedin the platelets 10 b may be calculated by using Equation (2):

Vol _(b)=β*exp(γ*FSC)  Equation (2)

-   -   wherein, FSC is the intensity of forward scattered light signal        of each individual event characterized in the platelets 10 b,        and β and γ are constants.

In another embodiment, the volume (Vol) of each particle characterizedin the platelet 10 b may be calculated by using Equation (3):

Vol _(c)=[1/(FSC*σ(2π)^(1/2))]exp(−(lnFSC−μ)²/2σ²)  Equation (3)

-   -   where, FSC is the intensity of forward scattered light signal of        each individual event characterized in the platelets 10 b, and μ        and σ are constants.

At step S2557, volume distribution data corresponding to the platelets10 b may be acquired based on the volume (Vol) of each particle in theparticle population characterized by the platelets 10 b and acorresponding number of particles. Further, a volume distribution curve,which is referred to as a derived volume histogram herein, may beacquired based on the volume distribution data of the platelets 10 b, asshown in FIG. 4C. Since the volume distribution data (or the derivedvolume histogram) of the platelets 10 b contains information aboutplatelets in the hemolyzed blood sample, the volume distribution data isconsidered as a form of the second platelet detection data herein.

Further, larger particles can be differentiated from smaller particlesin the derived volume histogram by using a preset derived volumeseparation threshold, wherein the derived volume separation thresholdmay be selected from values between 10-20 fL, such as 10 fL, 12 fL, 15fL or 20 fL. The inventors have found after repeated assumptions andexperiments that the larger particles are mainly part of platelets witha relatively large volume in the test blood sample. Since the electricalimpedance method cannot be used to differentiate among large platelets,schistocytes and microcytes with a similar volume, the abnormality ofthe first platelet detection data acquired by the electrical impedancedetection method can be effectively alarmed by comparing a portiongreater than the derived volume separation threshold in the derivedvolume histogram with that in the electrical impedance volume histogramacquired in the second exemplary implementation. Since the curve portionof the larger particles in the derived volume histogram separated by thederived volume separation threshold contains information about plateletsin the hemolyzed blood sample, it is also considered as a form of thesecond platelet detection data herein. Alternatively, characteristicparameters such as an area of the curve portion may also be acquiredbased on the curve portion of the larger particles in the derived volumehistogram, and the characteristic parameters are also a form of thesecond platelet detection data.

In an alternative implementation, the at least two types of opticalsignals acquired at step S235 include forward scattered light signals,side scattered light signals and fluorescent signals. Then, at stepS2557, based on the forward scattered light signals and the sidescattered light signals of the platelets 10 b, the volume of eachparticle in the platelet region may also be calculated by using the MieScattering Theory (ZHANG Wei, LU Yuan, DU Shiming, et. al., Analysis onMie Scattering Characteristics of Spherical Particles, OpticalTechnology, 2010-11: Volume 36 Issue 6: 936-939.), thereby acquiringvolume distribution data of the particle population characterized by theplatelets 10 b, that is, the second platelet detection data.Alternatively, a derived volume histogram may be acquired based on thevolume distribution data of the platelets 10 b. Alternatively, a curveportion of larger particles in the derived volume histogram may beacquired based on the derived volume histogram and a derived volumeseparation threshold, and information of larger platelets in the testblood sample may be acquired based on the curve portion. Obviously, inthe alternative implementation, the second platelet detection data maybe acquired by using Equation (1), Equation (2) or Equation (3) based onthe forward scattered light signals of the platelets 10 b.

The second platelet detection data of the test blood sample may beacquired by sequentially executing steps S2551-S2557 in step S255. Inthe second exemplary implementation, at step S270, the evaluation resultis acquired based on the difference between the first platelet detectiondata and the second platelet detection data. Accordingly, for the bloodanalysis system in the first exemplary implementation, the alarm module790 acquires the evaluation result based on the difference between thefirst platelet detection data and the second platelet detection data. Inorder to acquire the evaluation result, step S270 may further includethe following steps.

Step S2701: acquiring the first platelet detection data acquired at stepS250 and the second platelet detection data acquired at step S255. Itcan be understood that in an implementation, presentation forms of thefirst and second platelet detection data which can be used for directcomparison may be selectively acquired at step S2701, for example, curveportions with volumes greater than a certain preset volume separationthreshold in the electrical impedance volume histogram and the derivedvolume histogram, or, integral areas of the curve portions relative toabscissa “volume”. It can be understood that, in another implementation,the first and second platelet detection data in other presentation formsmay also be acquired at step S2701, for example, a half-peak width or ahalf-peak amplitude, and then after step S2701, at step S2703, thepresentation forms of the first and second platelet detection data arematched, and the presentation forms of the platelet detection data whichcannot be directly compared may be calculated and converted forcomparison.

Step S2705: acquiring the evaluation result based on the presentationforms of the first and second platelet detection data for directcomparison. The evaluation result may be a result acquired by comparingnumerical magnitudes and/or graphic differences between the firstplatelet detection data and the second platelet detection data. For theplatelet detection data in a numerical form, at step S2705, anevaluation value reflecting the difference degree between the firstplatelet detection data and the second platelet detection data may beacquired by calculating the two by a mathematical expression, and thenthe evaluation value is compared with a preset threshold to acquire theevaluation result that the evaluation value is greater than, equal to,or less than the preset threshold. For the platelet detection data in agraphic form (such as histogram), the evaluation result acquired at stepS2705 may be a preset qualitative description of the difference degreebetween the curves of the first platelet detection data and the secondplatelet detection data, such as “substantially similar” or“significantly different”. It can be understood that, contents of theevaluation result may include one or more analysis and comparisonresults, for example, may include a plurality of numerical evaluationresults of characteristic parameters that reflects information aboutplatelets in the blood sample.

It should be noted that the evaluation value may be a difference degreeof the second platelet detection data relative to the first plateletdetection data, or a difference degree of the first platelet detectiondata relative to the second platelet detection data. It should be notedthat methods for calculating the evaluation value is not limited to thatdisclosed herein. It can be understood that, the preset thresholddescribed at step S2705 is set according to a setting mode of theevaluation value. Taking that the platelet detection data is an integralarea value within a certain volume range in the volume histogram as anexample, the evaluation value (EV) may be a difference, an absolutedifference or a quotient between the second platelet detection data(PLT2) and the first platelet detection data (PLT1), or may also be areciprocal, a multiple or an exponent of the difference, the absolutedifference or the quotient. In an embodiment, EV=a*(PLT2/PLT1), where ais a preset coefficient. In another embodiment, EV=a*(PLT1/PLT2), wherea is a preset coefficient. In another embodiment, EV=(PLT1−PLT2)b, whereb is a preset coefficient. The evaluation value (EV) may also be othervalues that can reflect the difference between PLT1 and PLT2, forexample, EV=(PLT1−PLT2)/PLT1, EV=(PLT1−PLT2)/PLT2, etc.

In the second exemplary implementation, at step S280, whether theevaluation result acquired at step S270 meets the preset condition isdetermined. When the determination result is yes, step S290 is executedto provide an alarm for indicating that the first platelet detection isabnormal and/or the electrical impedance signal detection process isabnormal. When the determination result is no, the process ends.Accordingly, for the blood analysis system in the first exemplaryimplementation, the alarm module 790 determines whether the evaluationresult meets the preset condition: when the determination result is yes,namely the evaluation result meets the preset condition, outputs analarm for indicating that the first platelet detection is abnormaland/or the electrical impedance signal detection process is abnormal;when the determination result is no, ends the process. Information ofthe alarm for indicating that the first platelet detection is abnormaland/or the electrical impedance signal detection process is abnormalacquired by the alarm module 790 may be transmitted to the userinterface 90.

It can be understood that, under a normal condition (FIG. 5A), thedifference between the first platelet detection data acquired by theelectrical impedance method and the second platelet detection dataacquired by the optical method described in the present disclosure isrelatively small, that is, the evaluation result acquired by the systemsand methods provided by the present disclosure includes information thatthe difference between the first and second platelet detection data isrelatively small, and when the preset condition is that the first andsecond platelet detection data are significantly different, thedetermination result at step S280 is no, the process ends. Under anabnormal condition (FIG. 5B), such as an abnormal blood samplecontaining microcytes or an abnormality present in the electricalimpedance detection channel, there may be a significant differencebetween the first and second platelet detection data, and when thepreset condition is that the first and second platelet detection dataare significantly different, the determination result at step S280 isyes, the abnormality of the first platelet detection and/or theabnormality of the impedance channel signal detection process arealarmed.

Specifically, when the evaluation result acquired at step S270 is amagnitude relationship between the evaluation value and a presetthreshold, the preset condition set at step S280 may be that theevaluation value is greater than the preset threshold. When theevaluation result acquired at step S270 is a difference degree betweengraphs of the first and second platelet detection data, the presetcondition set at step S280 may be that the graphics of the first andsecond platelet detection data are significantly different. It can beunderstood that the preset condition may include a plurality of presetconditions. When the plurality of preset conditions is all met, thedetermination result at S280 is yes.

In the second exemplary implementation, alternatively, the step ofoutputting other detection results and/or intermediate results mayfurther be included. The detection results include but not limited tothe first platelet detection data acquired at step S250 and the secondplatelet detection data acquired at step S255. The intermediate resultsinclude but not limited to the scattergram acquired at step S255, theplatelet region in the scattergram, the derived volume histogram, thecurve portion of the larger particles separated by the derived volumeseparation threshold, and the evaluation value or evaluation resultacquired at step S270, etc.

It should be noted that the abnormality described herein may be causedby an abnormality of the blood analyzer. The abnormality of the bloodanalyzer includes but not limited to: an abnormality of the electricalimpedance detection unit, and an abnormality of the optical detectionunit. In this application, since the probability of an abnormality ofthe optical detection unit is generally low, an abnormality of theelectrical impedance detection unit can be prompted by comparing thefirst and second platelet detection data. Further, the first and secondplatelet detection data of a plurality of samples can be continuouslyrecorded and compared; and through statistical analysis, only when thedata of the plurality of samples are continuously inconsistent, anabnormality of the electrical impedance detection unit is promoted,thereby increasing accuracy of alarm.

In another embodiment, the second platelet detection may be performed byusing white blood cell detection or nucleated red blood cell detectionof an existing analyzer. That is, the second test sample may be a testsolution for classifying or counting white blood cells or countingbasophils or counting nucleated red blood cells. Since red blood cellsin the test solution are lysed and blood cells are stained by afluorescence dye, optical signals of each cell particle can also beacquired in optical detection. The inventors have found throughresearches that, in the scattergram acquired by the detection, there isalso a platelet region P, which can be applied in aforementioned methodsfor alarming. At the same time, a white blood cell classification resultcan be acquired. As shown in FIG. 11 , white blood cells aredifferentiated into four subpopulations: lymphocytes, monocytes,neutrophils and eosinophils based on the fluorescent signals, the sidescattered light signals and the forward scattered light signals.Further, in other implementations, basophils are differentiated fromother white blood cell subpopulations in the white blood cells based onthe scattered light signals and the fluorescent signals. In otherembodiments, the method may further include the steps of counting anumber of white blood cells and reporting the count of white blood cellsin the blood sample. Those skilled in the art should understand that,the method may further include the step of identifying nucleated redblood cells, immature cells or blast cells based on the scattered lightsignals and the fluorescent signals of the second test sample. Forexample, as shown in FIG. 12 , when the blood sample contains immaturecells, in the method, immature cells can be identified based on thescattered light signals and the fluorescent signals, and white bloodcells can further be differentiated into four subpopulations:lymphocytes, monocytes, neutrophils and eosinophils. Or, for example, asshown in FIG. 13 , nucleated red blood cells and white blood cells canbe identified and counted based on the scattered lights and thefluorescent signals.

It has been found through researches that the platelet region may alsobe differentiated by using a fluorescence-side scattered light (SFL-SSC)scattergram, as shown in FIG. 14 . Therefore, when a sample passesthrough a nucleated red blood cell detection unit, fluorescent signals,forward scattered light signals and side scattered light signals areacquired at the same time, the P region can be differentiated by using aSFL-SSC scattergram, and then a derived platelet volume histogram isacquired at least based on the forward scattered light signal of eachcell to obtained the second detection data.

A method for alarming an abnormality provided by a third exemplaryimplementation of the present disclosure will be described below.Compared with the method of the second exemplary implementationdescribed above, in the third exemplary implementation, a differentmethod for acquiring the second platelet detection data is adopted atstep S255 a. For the main analysis process and other steps of the thirdexemplary implementation, reference can be made to FIG. 3 and thecontents described above, which will not be repeated herein.

In the third exemplary implementation, at step S225 a, the secondplatelet detection data is acquired based on at least two types ofoptical signals of the second test sample, wherein the at least twotypes of optical signals include forward scattered light signals andfluorescent signals of the second test sample, red blood cells of whichare lysed. Specifically, step S255 a includes the following steps:

Step S2551 a: acquiring the at least two types of optical signals of thesecond test sample.

Step S2553 a: generating a scattergram of the second test sample basedon the at least two types of optical signals.

Step S2555 a: differentiating a white blood cell region from a plateletregion in the scattergram of the second test sample based on the atleast two types of optical signals. In the third exemplaryimplementation, the platelet region differentiated at step S2555 a is alarge platelet region P′, and the large platelet region P′ is a regionwhere large platelets in the second test sample appear in thescattergram. In an embodiment shown in FIG. 6A, the intensities of theforward scattered light signals of the large platelet region P′ aresubstantially less than that of the white blood cell region W, and aresubstantially greater than that of schistocytes at the lower left cornerof the scattergram. The intensities of the fluorescent signals of thelarge platelet region P′ are substantially less than that of the whiteblood cell region W. A platelet derived volume histogram may also beacquired by using the foregoing method at least based on the largeplatelet region P′, as shown in FIG. 6B. It should be noted that FIG. 6Bis a schematic diagram. For the sake of easy understanding, the leftpart of the curve is fitted.

Step S2557 a: acquiring the second platelet detection data of the bloodsample based on the large platelet region P′. In the third exemplaryimplementation, the second platelet detection data may be large plateletdetection data, such as volume distribution data of large platelets, acount of large platelets or other characteristic parameters that canreflect volume distribution of large platelets.

In an implementation, at step S2557 a, the volume distribution data oflarge platelets may be acquired based on the forward scattered lightsignals of a particle population characterized in the large plateletregion P′. Specifically, the forward scattered light signals may beconverted into a volume of each particle in the large platelet region P′by using Equation (1), Equation (2) or Equation (3), thereby acquiringthe volume distribution data of large platelets. In anotherimplementation of the third exemplary implementation, the at least twotypes of optical signals acquired at step S235 a include forwardscattered light signals, side scattered light signals and fluorescentsignals, and the volume of each particle in the large platelet region P′may also be calculated at step S2557 a based on the forward scatteredlight signals and the side scattered light signals of the particlepopulation characterized in the large platelet region P′ by using theMie Scattering Theory, thereby acquiring the volume distribution data oflarge platelets. Alternatively, a derived volume histogram of largeplatelets may be acquired based on the volume distribution data of largeplatelets.

Alternatively, a count value of large platelets may further becalculated based on the volume distribution data of large platelets. Inthe present disclosure, a volume threshold for defining large plateletsmay be set by users, and the volume threshold may be any numerical valuebetween 10-20 fL, for example, large platelets may be platelets with avolume greater than 10 fL, 12 fL, 15 fL or 20 fL. Those skilled in theart should understand that the range of the large platelet region P′ maybe accordingly changed based on the set volume threshold of largeplatelets. Alternatively, characteristic parameters reflecting volumedistribution of large platelets, such as count value of large platelets,volume distribution width of large platelets, may further be calculatedbased on the volume distribution data of large platelets.

In an implementation, a number of particles (or referred to as “eventnumber”) of the particle population characterized in the large plateletregion P′ may also be acquired at step S2557 a, and a count value oflarge platelets is acquired based on the number of particles.

In the third exemplary implementation, at step S270 a, the firstplatelet detection data acquired at step S250 and the second plateletdetection data acquired at step S255 a may be acquired, and anevaluation result is acquired based on a difference between the firstplatelet detection data and the second platelet detection data. It canbe understood that the second platelet detection data used for step S270a may be the volume distribution data of large platelets (such as thederived volume histogram of large platelets), the count value of largeplatelets or other characteristic parameters reflecting volumedistribution of large platelets. Accordingly, step S270 a may includethe step of pre-processing the first platelet detection data acquired atstep S250, thereby making the forms of the acquired first and secondplatelet detection data matched to acquire the evaluation result basedon the difference therebetween.

For other specific contents of the third exemplary implementation,reference can be made to the contents of the second exemplaryimplementation, which will not be repeated herein.

An alarm method provided by a fourth exemplary implementation of thepresent disclosure will be described below. Compared with the methodmentioned in the second implementation for acquiring the second plateletdetection data by using the platelet region, and the method mentioned inthe third exemplary implementation for acquiring the second plateletdetection data by using the large platelet region, in the fourthexemplary implementation, a different sample treatment method and adifferent data analysis method for acquiring the second plateletdetection data is adopt at step S225 b; specifically, the secondplatelet detection data includes information about platelets withvarious volumes in the second test sample, including a count value ofplatelets in the sample. For the main analysis process and other stepsof the fourth exemplary implementation, reference can be made to FIG. 3and the contents described above in the second exemplary implementation,which will not be repeated herein.

At step S225 b, the lytic reagent for preparing the second test sampleincludes a hemolytic agent for lysing red blood cells and a fluorescencedye for staining blood cells. In the fourth exemplary implementation, byselection of the hemolytic agent and/or the fluorescence dye, opticaldifferences between platelets and white blood cells and schistocytes inthe hemolyzed second test sample are more significant, thereby realizingdifferentiation and counting of platelets.

In an implementation, at step S225 b, blood cells in the blood sampleare specifically stained by using a membrane dye or a mitochondrial dye,and the second test sample is prepared by lysing red blood cells usingthe hemolytic agent mentioned in the forgoing exemplary implementations,thereby differentiating platelets in the second test sample based on theat least two types of optical signals. The membrane dye may compriseAlexa Fluor series dyes, other commercially available membrane dyes, andvariants using these dyes as parent. The mitochondrial dye may compriseRhodamine 123 dyes, Mitotracker series dyes, other commerciallyavailable mitochondrial dyes, and variants using these dyes as parent.FIG. 7A shows an FSC-FL scattergram of a second test sample stained byAlexa Fluor 488 dye. FIG. 7B shows an FSC-FL scattergram of a secondtest sample stained by Mitotracker Red dye. FIG. 7C shows an FSC-FLscattergram of a second test sample stained by Rhodamine 123 dye. FIG.7D shows an FSC-FL scattergram of a second test sample stained byMitotracker Deep Red dye. It can be understood that, in order to furtherhighlight differences among different particle populations, in thisimplementation, the coordinate axis of the scattergram generated at stepS255 b are logarithmic coordinate axis. As can be seen from FIGS. 7A-7D,by specific staining blood cells in blood sample using a membrane dye ora mitochondrial dye, a platelet region P″ can be differentiated in thescattergram. The platelet region P″ is a region where platelets in thesecond test sample appear in the scattergram.

In another implementation, at step S225 b, red blood cells are lysed byusing the hemolytic agent containing a glycoside compound disclosed inChinese Invention Patent ZL200910109215.6, and the second test sample isprepared by adjusting dosage of the hemolytic agent for enhancinghemolysis intensity and staining blood cells using a nucleic acid dye,thereby differentiating platelets in the second test sample based on theat least two types of optical signals. All the contents disclosed inChinese Invention Patent ZL200910109215.6 are incorporated herein byreference. The dye may be selected from the membrane dyes or themitochondrial dyes described in the foregoing exemplary implementations,or may be selected from the fluorescence dyes mentioned in the foregoingpatents, or from other fluorescence dyes suitable for staining whiteblood cells or reticulocytes, for example, fluorescence dye SYTO9.

In this implementation, the hemolytic agent includes a glycosidecompound, a nonionic surfactant and an anionic organic compound.

The glycoside compound is selected from saponin and alkyl glycosidecompounds. The glycoside compounds have the general formulaR—(CH2)n-CH3, where n is an integer of 5-17, preferably, n is an integerof 6-14; R is a monosaccharide, a monosaccharide polymer or apolysaccharide. More specifically, R may be selected from commonly usedcarbohydrates, such as glucose, rhamnose, galactose, arabinose, xylose,maltose, mannose, ribose, lyxose, fucose, etc., and their deoxy sugar,and polymers thereof.

The nonionic surfactant has the general formula R1-R2-(CH2CH2O)n-H,where, R1 is a C8-C23 alkyl group or an alkenyl group. Preferably, R1 isa linear alkyl group, which is selected from octyl, decyl, lauryl,tetradecyl, hexadecyl and stearyl. Further preferably, R1 is a linearalkyl group, which is selected from lauryl, tetradecyl and hexadecyl. R2is selected from —O—,

or —COO—, and n is an integer of 10-30.

The anionic organic compound is selected from anionic organic compoundsof acids or salts with one or more hydroxy or sulfonic groups.

FIG. 8A shows an FSC-SFL scattergram of a second test sample acquired byan embodiment of this implementation, wherein the lytic reagent used atstep S225 b includes a hemolytic agent and a nucleic acid dye describedabove. Specifically, in the embodiment shown in FIG. 8A, components andtheir concentrations of the lytic reagent are as follows:

Fluorescence dye SYTO9 1.0 ppm Saponin 0.6 g/L TRIS 40 Mm Sodium citrate5 g/L Polyoxyethylene (23) Di-n-hexadecyl ether 0.5 g/L

The pH value of the lytic reagent is 7.5. 20 μL blood sample was addedinto 1 mL foregoing lytic reagent and incubated for 60 seconds at 45°C., and forward scattered light signals and 90-degree side fluorescent(SFL) signals were collected at an excitation wavelength of 488 nm.Based on the forward scattered light signals and the fluorescentsignals, the scattergram shown in FIG. 8A can be acquired, and theplatelet region P″ can further be differentiated in the scattergram. Theplatelet region P″ is a region where platelets in the second test sampleappear in the scattergram. It can be understood that, in order tofurther highlight differences among different particle populations, inthis implementation, coordinate axis of the scattergram generated atstep S255 b are logarithmic coordinate axis.

In other implementations, the above two implementations may also be usedin combination. In other words, the lytic reagent used at step S225includes a hemolytic agent and a fluorescence dye. The hemolytic agentincludes a glycoside compound, a nonionic surfactant and an anionicorganic compound. The fluorescence dye is selected from membrane dyes ormitochondrial dyes.

Please refer again to the flowchart of the method of the presentdisclosure shown in FIG. 3 . As seen from the above, in the fourthexemplary implementation, at step S255 b, the scattergram shown in FIG.7A-7D or FIG. 8A may be generated based on the at least two types ofoptical signals, including the forward scattered light signals and thefluorescent signals. At step S255 b, a white blood cell region and aplatelet region P″ are differentiated from each other in the scattergramof the second test sample based on the at least two types of opticalsignals, and then the second platelet detection data of the blood sampleis acquired based on the platelet region P″.

In an implementation, volume distribution data of platelets may beacquired based on the forward scattered light signals of a particlepopulation characterized in the platelet region P″. Specifically, theforward scattered light signals may be converted into a volume of eachparticle in the platelet region P″ by using Equation (1), Equation (2)or Equation (3), thereby acquiring the volume distribution data ofplatelets. In another implementation, the at least two types of opticalsignals acquired at step S235 b include forward scattered light signals,side scattered light signals and fluorescent signals, and the volume ofeach particle in the platelet region P″ may also be calculated at stepS225 b based on the forward scattered light signals and the sidescattered light signals of the particle population characterized in theplatelet region P″ by using the Mie Scattering Theory, thereby acquiringthe volume distribution data of platelets. Alternatively, a derivedvolume histogram of platelets may be acquired based on the volumedistribution data of platelets. Alternatively, characteristic parametersreflecting volume distribution of platelets further may be calculatedbased on the volume distribution data of platelets, such as a countvalue of platelets, a mean platelet volume and a volume distributionwidth. In another implementation, the count value of platelets may beacquired by acquiring a number of particles of the particle populationcharacterized in the platelet region P″.

It can be understood that the second platelet detection data acquired atstep S255 b may be the volume distribution data of platelets (such asthe derived volume histogram of platelets), or may be the characteristicparameters reflecting volume distribution of platelets (such as thecount value of platelets, the mean platelet volume and the volumedistribution width, etc.).

Similarly, based on the first and second platelet detection dataacquired at steps S250 and S255 b, steps S270 b-S290 b are executed insuccession to provide an alarm for abnormalities during the blood sampleanalysis process. For relevant specific contents reference can be madeto the above, which will not be repeated herein. In this application,abnormality alarming includes: providing a prompt for indicating thatthe electrical impedance detection unit may be abnormal in the presentsample detection or that the present detection result is unreliable dueto the abnormality of the electrical impedance detection unit; orproviding a prompt for indicating that the electrical impedancedetection unit and/or the optical detection unit are/is abnormal in thepresent sample detection or that the present detection result isunreliable due to the abnormality.

Those skilled in the art should understand that all or part of the stepsin the second, the third or the fourth exemplary implementation may beimplemented by instructing related hardware of a blood analyzer throughcomputer programs. The computer programs may be stored in acomputer-readable storage medium and loaded into the blood analyzerhaving corresponding hardware system. When the computer programs areexecuted by a processor, the blood analyzer executes the analysis methodfor blood sample disclosed in the second, the third or the fourthexemplary implementation of the present disclosure.

The first aspect of the present disclosure further provides a bloodanalyzer. The blood analyzer includes a processor and a non-volatilecomputer-readable storage medium. The processor is configured to executecomputer programs stored in the non-volatile computer-readable storagemedium to implement the steps of the analysis method according to thesecond or the third or the fourth exemplary implementation.

The first aspect of the present disclosure further provides anon-volatile computer-readable storage medium storing computer programsthereon, wherein the computer programs, when executed by a processor,implement the steps of the analysis method of the second, the third orthe fourth exemplary implementation. For the specific steps, referencecan be made to various implementations and embodiments described above,which will not be repeated herein. Therefore, the analysis method of thesecond, the third or the fourth exemplary implementation may beimplemented in the form of software function units and sold or used asan independent product.

The products and methods provided by the first aspect of the presentdisclosure can, based on the existing five-classification blood analysissystem, respectively obtain detection data of platelets by usingelectrical impedance detection channel and white blood cellclassification detection channel (for example, DIFF channel of BC-6800blood analyzer produced by Shenzhen Mindray Bio-Medical Electronics Co.,Ltd.), and provide an alarm for indicating an abnormal detection resultby comparing the first and second platelet detection data acquired bythe two detection channels. The products and methods provided by thefirst aspect of the present disclosure do not require a separatedetection channel, and can provide users with more abundant detectioninformation in a real-time manner, remind the users to perform areexamination or recheck on abnormal platelet detection data, therebyincreasing accuracy of platelet detection, without increasing the costsof the blood analysis system.

A second aspect of the present disclosure relates to a method, systemand storage medium for providing an alarm for an abnormality of plateletdetection and/or an abnormality of impedance channel by using electricalimpedance signals and scattered light signals of a blood sample.Compared with the first aspect of the present disclosure, the secondaspect of the present disclosure provides a product and method forproviding an alarm for an abnormality of platelet detection and/or anabnormality of impedance detection channel, without using a fluorescencedye. It should be noted that in the second aspect of the presentdisclosure, a fluorescence dye may also be added to prepare a secondtest sample, and whether to use a fluorescence dye would not affect therealization of corresponding implementations.

A fifth exemplary implementation of the present disclosure provides analarm method. Please refer again to the flowchart shown in FIG. 3 . Thealarm method includes the following steps:

Step S200: providing a blood sample.

Step S220: mixing a first aliquot of the blood sample with a diluentagent to obtain a first test sample for first platelet detection.

Step S225 c: mixing a second aliquot of the blood sample with a lyticreagent to obtain a second test sample for second platelet detection,wherein the lytic reagent includes a hemolytic agent for lysing redblood cells.

Step S230: detecting electrical impedance signals of the first testsample.

Step S235 c: detecting at least two types of optical signals of thesecond test sample. The at least two types of optical signals includefirst scattered light signals and second scattered light signals,wherein the first scattered light signals are forward scattered lightsignals, and the second scattered light signals are at least one type ofmedium-angle scattered light signals and side scattered light signals.

Step S250: are acquiring first platelet detection data of the bloodsample based on the electrical impedance signals acquired at step S230.

Step S255 c: acquiring second platelet detection data of the bloodsample based on the at least two types of optical signals obtained atstep S235.

Step S270 c: acquiring an evaluation result based on a differencebetween the first platelet detection data and the second plateletdetection data.

Step S280: determining whether the evaluation result meets a presetcondition. When the determination result is yes, step S290 is executedto provide an alarm for indicating that the first platelet detection isabnormal and/or the electrical impedance signal detection is abnormal.When the determination result is no, the process ends.

Those skilled in the art should understand that all or part of the stepsmay be implemented by the blood analysis system shown as FIG. 1 throughcomputer programs.

At step S225 c, the second aliquot of the blood sample is mixed with thehemolytic agent to obtain the second test sample. The hemolytic agentmay be any one of existing hemolysis reagents used by automated bloodanalyzers for classifying white blood cells, or may be any one of acationic surfactant, a nonionic surfactant, an anionic surfactant and anamphiphilic surfactant or any combination thereof.

At step S235 c, the forward scattered light signals, and at least onetype of the medium-angle scattered light signals and the side scatteredlight signals of the second test sample may be acquired by one or moreoptical detectors. The medium-angle scattered light signals may bedetected by an optical detector at an angle between forward scatteredlight and side scattered light. The medium-angle scattered light signalsmay be low medium-angle scattered light signals detected at an anglerange from about 8° to about 24° relative to an incident beam, or highmedium-angle scattered light signals detected at an angle range fromabout 25° to about 65° relative to the incident beam. As mentionedabove, the forward scattered light signals may be detected at an anglerange from about 1° to about 10° relative to the incident beam,preferably, the forward scattered light signals may be detected at anangle range from about 2° to about 6° relative to the incident beam. Theside scattered light signals may be detected at an angle of about 90°relative to the incident beam, alternatively, the side scattered lightsignals may also be detected at an angle range from about 65° to about115° relative to the incident beam.

Similar to the methods of the first aspect of the present disclosure,step S255 c may include the following steps:

Step S2551 c: acquiring the at least two types of optical signals of thesecond test sample, that is, the forward scattered light signals and atleast one type of the medium-angle scattered light signals and the sidescattered light signals.

Step S2553 c: generating a scattergram of the second test sample basedon the at least two types of optical signals.

Step S2555 c: differentiating a white blood cell region from a plateletregion in the scattergram acquired at step S2553 c based on the at leasttwo types of optical signals.

Step S2557 c: acquiring the second platelet detection data of the bloodsample based on the platelet region acquired at step S2555 c.

In an implementation, similar to the second exemplary implementationdescribed above, the platelet region P differentiated at step S2555 cincludes a region where the platelets appear in the scattergram, whichmay include a region where impurity particles like schistocytes appearin the scattergram. At step S2557 c, the forward scattered light signalsof a particle population characterized in the platelet region P areconverted into a volume of each particle in the platelet region P byusing Equation (1), Equation (2) or Equation (3), thereby acquiringvolume distribution data of platelets. When the second scattered lightsignals are side scattered light signals, the volume of each particle inthe platelet region P may also be calculated at step S2557 c by usingthe Mie Scattering Theory based on the forward scattered light signalsand the side scattered light signals of the particle populationcharacterized in the platelet region P, thereby acquiring the volumedistribution data of platelets. The volume distribution data may berepresented in a numerical form or in a graphical form, such as aderived volume histogram.

Further, larger particles can be differentiated from smaller particlesin the derived volume histogram by using a preset derived volumeseparation threshold. The derived volume separation threshold may beselected from values between 10-20 fL, such as 10 fL, 12 fL, 15 fL or 20fL. In the separated derived volume histogram, a curve portion of thelarger particles contains information about platelets in hemolyzed bloodsample and may be regarded as a form of the second platelet detectiondata. Alternatively, characteristic parameters such as an area of thecurve portion may also be acquired based on the curve portion of thelarger particles in the derived volume histogram. The characteristicparameters may also be regarded as a form of the second plateletdetection data.

In another implementation, similar to the third exemplary implementationdescribed above, the platelet region differentiated at step S2555 c is alarge platelet region P′, and the large platelet region P′ is a regionwhere large platelets in the second test sample appear in thescattergram. FIG. 9 shows an FSC-SSC scattergram generated by anembodiment of this implementation. At step S2557 c, the scattered lightsignals of a particle population characterized in large platelet regionP′ may be converted into a volume of each particle in the large plateletregion P′ by using Equation (1), Equation (2), Equation (3) or MieScattering Theory, thereby acquiring volume distribution data of largeplatelets. Alternatively, a derived volume histogram of large plateletsmay be acquired based on the volume distribution data of largeplatelets. Alternatively, the characteristic parameters reflectingvolume distribution of large platelets, such as a count value of largeplatelets, a volume distribution width of large platelets, may also becalculated based on the volume distribution data of large platelets.Alternatively, a count value of large platelets may also be acquired atstep S2557 c by acquiring a number of particles of the particlepopulation characterized in the large platelet region P′. It can beunderstood that, in the implementation, the second platelet detectiondata may be the volume distribution data of large platelets (such asderived volume histogram of large platelets), the count value of largeplatelets or other characteristic parameters reflecting volumedistribution of large platelets.

In another implementation, similar to the fourth exemplaryimplementation mode described above, the platelet region differentiatedat step S2555 c is a platelet region P″, and the platelet region P″ is aregion where platelets in the second test sample appear in thescattergram. In the implementation, at step S225 c, the second testsample is prepared by using the hemolytic agent containing a glycosidecompound disclosed in Chinese Invention Patent ZL200910109215.6, withoutusing a nucleic acid dye. It has been found through researches that, byonly increasing hemolysis intensity without using a dye, the plateletregion P″ may appear in the scattergram based on the two types ofscattered lights. FIG. 8B shows an FSC-SSC scattergram acquired by anembodiment of the implementation. At step S2557 c, volume distributiondata of platelets may be acquired based on the forward scattered lightsignals (or the forward scattered light signals and the side scatteredlight signals) of the particle population characterized in the plateletregion P″, and a derived volume histogram of platelets andcharacteristic parameters reflecting volume distribution of platelets,such as a count value of the platelets, a mean platelet volume and avolume distribution width, may also be acquired based on the volumedistribution data of platelets. At step S2557 c, a count value ofplatelets may also be acquired by acquiring a number of particles of theparticle population characterized in the platelet region P″.

In the fifth exemplary implementation, the evaluation result is acquiredat step S270 c by analyzing the difference between the first plateletdetection data acquired at step S250 and the second platelet detectiondata acquired at step S255 c. At step S280, whether the evaluationresult acquired at step S270 c meets a preset condition is determined.When the determination result is yes, step S290 is executed to providean alarm for indicating the first platelet detection is abnormal and/orthe electrical impedance signal detection is abnormal. When thedetermination result is no, the process ends. For specific contents ofsteps S270 c-290, reference can be made to the contents of the second,the third or the fourth exemplary implementation described above, whichwill not be repeated herein.

In the fifth exemplary implementation, alternatively, the step ofoutputting other detection results and/or intermediate results mayfurther be included. The detection results include but not limited tothe first platelet detection data acquired at step S250 and the secondplatelet detection data acquired at step S255 c. The intermediateresults include but not limited to the scattergram acquired at step S255c, the platelet region in the scattergram, the derived volume histogram,the curve portion of the larger particles separated by the derivedvolume separation threshold, and the evaluation value or the evaluationresult acquired at step S270 c, etc.

Further, in the above exemplary implementations, particularly in thefourth and the fifth exemplary implementations, a count value ofplatelets can be acquired. However, the probability of an abnormality ofthe optical detection unit is generally low, the count value ofplatelets acquired from the second platelet detection data can beoutputted and reported to users in order to report the detection resultof the test sample as soon as possible. That is, when the evaluationresult is that there is no significant difference therebetween, thecount value of platelets acquired from the first platelet detection datais outputted; when the evaluation result is that there is a significantdifference therebetween, the count value of platelets acquired from thesecond platelet detection data is outputted. Preferably, the result canbe marked to prompt the users that the result contains the count valueof platelets acquired by the optical detection method under thehemolysis condition, so as to be differentiated from the count value ofplatelets acquired by the electrical impedance method.

Those skilled in the art should understand that all or part of the stepsin the fifth exemplary implementation can be implemented by instructingrelated hardware of a blood analyzer through computer programs. Thecomputer programs may be stored in a computer-readable storage mediumand loaded into the blood analyzer having corresponding hardware system.When the computer programs are executed by a processor, the bloodanalyzer executes the analysis method for blood sample disclosed in thefifth exemplary embodiment of the present disclosure.

The second aspect of the present disclosure further provides a bloodanalyzer. The blood analyzer includes a processor and a non-volatilecomputer-readable storage medium. The processor is configured to executecomputer programs stored in the non-volatile computer-readable storagemedium to implement the steps of the analysis method of the fifthexemplary implementation.

The second aspect of the present disclosure further provides anon-volatile computer-readable storage medium storing computer programsthereon, wherein the computer programs, when executed by a processor,implement the steps of the analysis method of the fifth exemplaryimplementation. For the specific steps, reference can be made to variousimplementations and embodiments described above, which will not berepeated herein. Therefore, the analysis method of the fifth exemplaryimplementation may be implemented in the form of software function unitsand sold or used as an independent product.

Corresponding to the fifth exemplary implementation, the second aspectof the present disclosure further provides a blood analysis system.Please refer to FIG. 1 again, the blood analysis system includes asample collection unit 10, a sample treatment device a sample detectiondevice 50, a data analysis module 70 and a user interface 90.

The sample treatment device 30 includes at least one mixing chamber,which is configured to mix a first aliquot of a blood sample with adiluent agent to obtain a first test sample, and mix a second aliquot ofthe blood sample with a lytic reagent to obtain a second test sample.The lytic reagent includes a hemolytic agent for lysing red blood cells.

The sample detection device 50 includes an electrical impedancedetection unit 51 and an optical detection unit 53. The electricalimpedance detection unit is configured to detect electrical impedancesignals of the first test sample. The optical detection unit 53 isconfigured to detect at least two types of optical signals of the secondtest sample. The at least two types of optical signals include firstscattered light signals and second scattered light signals, wherein thefirst scattered light signals are forward scattered light signals, andthe second scattered light signals are at least one type of medium-anglescattered light signals and side scattered light signals.

The data analysis module 70 includes a signal acquisition module 750, aclassification and counting module 770 and an alarm module 790. Thesignal acquisition module 750 acquires the electrical impedance signalsof the first test sample and the at least two types of optical signalsof the second test sample. The classification and counting module 770acquires first platelet detection data of the blood sample based on theelectrical impedance signals. The classification and counting module 770generates a scattergram of the second test sample based on the at leasttwo types of optical signals, differentiates a white blood cell regionfrom a platelet region in the scattergram based on the at least twotypes of optical signals, and then acquires second platelet detectiondata of the blood sample based on the platelet region. The alarm module790 acquires an evaluation result based on a difference between thefirst platelet detection data and the second platelet detection data,and then determines whether the evaluation result meets a presetcondition. When the determination result is yes, an alarm for indicatingthat the platelet detection is abnormal and/or the impedance channel isabnormal is provided. When the determination result is no, the processends.

For specific implementations of other specific structures and functionmodules of the blood analysis system, reference can be made tocorresponding contents described above, which will not be repeatedherein.

Compared with the products and methods provided by the first aspect ofthe present disclosure, the blood analysis system, analysis method,blood analyzer and storage medium provided by the second aspect canprovide an alarm for indicating that the platelet detection is abnormaland/or the impedance detection is abnormal without using a fluorescencedye, and can provide users with more abundant detection information, andremind the users to perform a reexamination or recheck on the plateletdetection results without increasing the costs of the blood analysissystem and the costs of the reagents used in the blood analysis process,thereby increasing accuracy of platelet detection or discovering anabnormality in the sample analyzer in good time.

FIG. 10 is an overall stereoscopic diagram of a blood analysis systemprovided the present disclosure. As shown in FIG. 10 , the bloodanalysis system includes a first housing 100, a second housing 200, asample collection unit 10, a sample treatment device a sample detectiondevice 50, a data analysis module 70 and a user interface 90. In theimplementation, the sample detection device 50 and the data analysismodule 70 are arranged inside the second housing 200, and arerespectively arranged on both sides of the second housing 200. Thesample treatment device 30 is arranged inside the first housing 100. Theuser interface 90 and the sample collection unit 10 are arranged on theouter surface of the first housing 100.

The above embodiments are the preferred implementations of the presentdisclosure, but the present disclosure is not limited to the aboveembodiments, and the above implementations are only for interpretingclaims. Any changes or replacements that can be easily conceived bythose skilled in the art within the technical scope disclosed in thepresent disclosure are included within the protection scope of thepresent disclosure.

What is claimed is:
 1. A blood analysis system, comprising: a sampletreatment device comprising at least one mixing chamber for mixing afirst aliquot of a blood sample with a diluent agent to prepare a firsttest sample for first platelet detection, and for mixing a secondaliquot of the blood sample with a lytic reagent to prepare a secondtest sample for second platelet detection, wherein red blood cells inthe second test sample are lysed; a sample detection device comprisingan electrical impedance detection unit and an optical detection unit,wherein the electrical impedance detection unit includes an aperture andan electrical impedance detector, and the electrical impedance detectoris configured to detect electrical impedance signals of the first testsample passing through the aperture, and the optical detection unitincludes an optical flow chamber, a light source and an opticaldetector, wherein the optical flow chamber is in fluid communicationwith the at least one mixing chamber, the light source is configured todirect a light beam to the optical flow chamber, and the opticaldetector is configured to detect at least two types of optical signalsof the second test sample passing through the optical flow chamber; adata analysis module comprising a signal acquisition module, aclassification and counting module and an alarm module; wherein thesignal acquisition module is configured to acquire the electricalimpedance signals of the first test sample and the at least two types ofoptical signals of the second test sample; the classification andcounting module is configured to acquire first platelet detection dataof the blood sample based on the electrical impedance signals, generatea scattergram of the second test sample based on the at least two typesof optical signals, differentiate a white blood cell region from aplatelet region in the scattergram based on the at least two types ofoptical signals, and acquire second platelet detection data of the bloodsample based on the platelet region; and the alarm module is configuredto acquire an evaluation result based on a difference between the firstplatelet detection data and the second platelet detection data,determine whether the evaluation result meets a preset condition, andprovide an alarm for indicating that an abnormality is present in thefirst platelet detection and/or an abnormality is present in theelectrical impedance detection unit, when the evaluation result meetsthe preset condition.
 2. The blood analysis system according to claim 1,wherein the alarm module is configured to output a prompt that theabnormality of the first platelet detection is caused by the abnormalityin the electrical impedance detection unit and/or that the firstplatelet detection result is unreliable.
 3. The blood analysis systemaccording to claim 1, wherein the lytic reagent comprises a hemolyticagent for lysing red blood cells and a fluorescence dye for stainingblood cells, the at least two types of optical signals comprise forwardscattered light signals and fluorescent signals, and the opticaldetection unit comprises at least one scattered light detector and atleast one fluorescent detector; or wherein the lytic reagent comprises ahemolytic agent for lysing red blood cells, the at least two types ofoptical signals comprise first scattered light signals and secondscattered light signals, wherein the first scattered light signals areforward scattered light signals, and the second scattered light signalsare at least one type of medium-angle scattered light signals and sidescattered light signals, and the optical detection unit comprises atleast two scattered light detectors.
 4. The blood analysis systemaccording to claim 3, wherein the classification and counting module isconfigured to acquire a derived platelet volume histogram as the secondplatelet detection data based on at least the forward scattered lightsignals of a particle population in the platelet region; or theclassification and counting module is configured to acquire the secondplatelet detection data of the blood sample based on a number ofparticles in the platelet region.
 5. The blood analysis system accordingto claim 1, wherein the platelet region comprises a large plateletregion, the second platelet detection data comprises second largeplatelet data, and the second platelet detection data of the bloodsample is acquired by using the large platelet region.
 6. The bloodanalysis system according to claim 1, wherein the first plateletdetection data comprises at least one characteristic parameter of firstplatelet volume distribution data, and the second platelet detectiondata comprises at least one characteristic parameter of second plateletvolume distribution data.
 7. The blood analysis system according toclaim 1, wherein the lytic reagent comprises a hemolytic agent forlysing red blood cells and a fluorescence dye for staining blood cells,the at least two types of optical signals comprise scattered lightsignals and fluorescent signals, the optical detection unit comprises atleast one scattered light detector and at least one fluorescentdetector, and the classification and counting module is furtherconfigured to classify white blood cells into white blood cellsubpopulations, or count white blood cells or identify nucleated redblood cells or immature cells or basophils according to the scatteredlight signals and the fluorescent signals; or the lytic reagentcomprises a hemolytic agent for lysing red blood cells, the at least twotypes of optical signals comprise first scattered light signals andsecond scattered light signals, wherein the first scattered lightsignals are forward scattered light signals, and the second scatteredlight signals are at least one type of medium-angle scattered lightsignals and side scattered light signals, the optical detection unitcomprises at least two scattered light detectors, and the classificationand counting module is further configured to classify white blood cellsinto white blood cell subpopulations or identify basophils according tothe first scattered light signals and the second scattered lightsignals.
 8. The blood analysis system according to claim 1, wherein thealarm module is configured to: compare the first platelet detection datawith the second platelet detection data to obtain a graphic differencedegree therebetween, determine whether the graphic difference degreemeets a preset condition; or acquire numerical information of the firstplatelet detection data and the second platelet detection data,calculate an evaluation value by using the numerical information,wherein the evaluation value is used to reflect a difference degreebetween the first platelet detection data and the second plateletdetection data; and determine whether the evaluation value meets apreset condition.
 9. The blood analysis system according to claim 1,further comprising a user interface for: outputting the first plateletdetection data if there is no alarm for abnormality; and outputting thesecond platelet detection data if there is an alarm for abnormality.